text: import os
  
  # Support Directories
  base_store = '../base_store'
  saved_dataframes = 'saved_dataframes'
  saved_features = 'saved_features'
  saved_modelconfigs = 'saved_modelconfigs'
  saved_models = 'saved_models'
  clean_audio = 'clean_audio'
  saved_training_metrics_logs = 'saved_training_metrics_logs'
  log_dir = 'logs'
  
  # Genders
  gender_male = 'male'
  gender_female = 'female'
  gender_nonconformity = "nonconformity"
  
  # Databases
  database_ravdess = 'ravdess'
  database_emodb = 'emodb'
  database_cremad = 'cremad'
  database_shemo = 'shemo'
  
  # Datasets
  dataset_ravdess_male = 'ravdess_m'
  dataset_ravdess_female = 'ravdess_f'
  dataset_emodb_male = 'emodb_m'
  dataset_emodb_female = 'emodb_f'
  dataset_cremad_male = 'cremad_m'
  dataset_cremad_female = 'cremad_f'
  dataset_shemo_male = 'shemo_m'
  dataset_shemo_female = 'shemo_f'
  
  # Database audio sample paths
  main_databases_path = '../../../Resources/Databases'
  smpl_data_path_ravdess = os.path.join(main_databases_path, "RAVDESS_Audio")
  smpl_data_path_emodb = os.path.join(main_databases_path, "EmoDB", "wav")
  smpl_data_path_cremad = os.path.join(main_databases_path, "CREMA-D", "AudioWAV")
  info_path_cremad = os.path.join(main_databases_path, "CREMA-D", "VideoDemographics.csv")
  smpl_data_path_shemo = os.path.join(main_databases_path, "ShEMO")
  
  # Primary Emotions
  N = "neutral"
  C = "calm"
  H = "happy"
  S = "sad"
  A = "angry"
  F = "fearful"
  D = "disgust"
  Su = "surprised"
  B = "bored"
  Non = "none"
  
  # Status
  original = 'original'
  clean = 'clean'
  
  # Modes
  mode_write = 'write'
  mode_read = 'read'
  
  # Cleaning Parameters
  resample_rate = 16000
  step_size = int(resample_rate/10)
  
  # Model Modes
  ml_mode_convolutional = 'convolutional'
  